Chronic non-bacterial prostatitis (CNP) is a common urologic disease that is linked to the development of prostate cancer. Long non-coding RNA (lncRNA) GAS5 has been identified to mediate cell proliferation in prostate cancer, although its role in CNP is still unclear. Human prostate epithelial cell line RWPE-1 was induced by lipopolysaccharide (LPS) to mimic CNP model in vitro. Real-time PCR was performed to determine the expression of GAS5 and COX-2, while western blotting was used to evaluate the protein expression of COX-2. The interaction between GAS5 and COX-2 was determined using RNA pull-down and RNA immunoprecipitation (RIP). Cell proliferation was determined using MTT assay. The expression of GAS5 was decreased, while COX-2 was increased in prostatitis tissues and in LPS-induced RWPE-1 cells. The overexpression of GAS5 suppressed the protein level of COX-2, and inhibited cell proliferation of LPS-induced RWPE-1 cells and HPECs, which was rescued by the co-transfection with pcDNA-GAS5 and pcDNA-COX-2. GAS5 was confirmed to promote the ubiquitination of COX-2, and the in vivo GAS5-overexpressed CNP rat model decreased the motor scores, the volume of prostate tissues, the average number of inflammatory cells, prostatic proliferation, and COX-2 expression. Our findings revealed that overexpression of GAS5 inhibited cell proliferation via negatively regulating the expression of COX-2, thus alleviating the progression of CNP.

Background: Kidney transplantation is an optimal method for treatment of end-stage kidney failure. However, kidney transplant rejection (KTR) is commonly observed to have negative effects on allograft function. MicroRNAs (miRNAs) are small non-coding RNAs with regulatory role in KTR genesis, the identification of miRNA biomarkers for accurate diagnosis and subtyping of KTR is therefore of clinical significance for active intervention and personalized therapy. Methods: In this study, an integrative bioinformatics model was developed based on multi-omics network characterization for miRNA biomarker discovery in KTR. Compared with existed methods, the topological importance of miRNA targets was prioritized based on cross-level miRNA-mRNA and protein–protein interaction network analyses. The biomarker potential of identified miRNAs was computationally validated and explored by receiver-operating characteristic (ROC) evaluation and integrated “miRNA-gene-pathway” pathogenic survey. Results: Three miRNAs, i.e., miR-145-5p, miR-155-5p, and miR-23b-3p, were screened as putative biomarkers for KTR monitoring. Among them, miR-155-5p was a previously reported signature in KTR, whereas the remaining two were novel candidates both for KTR diagnosis and subtyping. The ROC analysis convinced the power of identified miRNAs as single and combined biomarkers for KTR prediction in kidney tissue and blood samples. Functional analyses, including the latent crosstalk among HLA-related genes, immune signaling pathways and identified miRNAs, provided new insights of these miRNAs in KTR pathogenesis. Conclusions: A network-based bioinformatics approach was proposed and applied to identify candidate miRNA biomarkers for KTR study. Biological and clinical validations are further needed for translational applications of the findings.

Introduction: The aim of this study was to compare the detection performance of mNGS against that of conventional tests (CT) in patients suffering from infection after kidney transplantation.Methods: A total of 138 samples from 85 kidney transplant patients with acute or chronic infections were simultaneously analyzed using mNGS and CT from July 2021 to August 2023.Results: Compared with CT, mNGS demonstrated a higher sensitivity (95.96% vs. 27.27%) but lower specificity (48.72% vs. 84.62%) in pathogen detection. Moreover, mNGS exhibited significant advantages in detecting mixed and rare infections. The pathogens commonly identified in kidney transplant patients were severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), followed by Pneumocystis jirovecii and Cytomegalovirus (CMV). mNGS guided the precise clinical diagnosis in 89.13% of cases and assisted in altering therapeutics from empirical antibiotic approaches to personalized plans in 56.10% of cases, including treatment escalation (40.65%), initiation (11.38%), drug adjustment (3.25%), and de-escalation (0.81%).Discussion: Our study demonstrated the superior detection performance of mNGS and its significant clinical value. This reflected the great potential of mNGS as a complementary clinical detection technology for kidney transplant patients.

Background: During the COVID-19 pandemic, COVID-19 infection has severely damaged the transplanted kidney function and health of kidney transplant patients. This study aims to investigate the clinical characteristics, risk factors and predictors of severe COVID-19 in patients after kidney transplantation. Material and Methods: The clinical data of patients with COVID-19 after kidney transplantation were collected from December 2022 to January 2023 at the First Affiliated Hospital of Soochow University. Logistic regression analysis was performed to identify risk factors for severe disease and to construct a nomogram model. Concurrently, metagenomic next-generation sequencing (mNGS) was employed to detect the sputum microbiome. Results: A total of 58 patients were enrolled and were categorized into the common group (n=35) and the severe group (n=23) based on infection severity. The common group comprised 23 males with a mean age of 45.60 ± 9.11 years, while the severe group included 16 males with a mean age of 48.22 ± 9.95 years. Multivariate logistic analysis revealed that days of fever before hospitalization, C-reactive protein (CRP) and interleukin-10 (IL-10) on admission were significantly independent risk factors for severity, with an area under the ROC curve at 0.906. Comparison of the sputum microbiome revealed that there were no significant differences in α and β diversity between the two groups. Streptococcus parasanguinis was significantly more abundant in the specimens from the severe group, while Gemella sanguinis and Gemella haemolysans were significantly more abundant in the common group. Conclusion: The severity of COVID-19 in kidney transplant patients is associated with days of fever before hospitalization, and the levels of CRP and IL-10 at admission, which also alter the abundance of certain species in the sputum microbiome. Therefore, it is necessary to actively monitor the clinical indicators of kidney transplant patients admitted with COVID-19 to reduce the risk of progression to severe disease.

Background: Pulmonary infection is a common and severe post-transplant complication in kidney transplant recipients (KTRs). Their long-term immunosuppression results in an extremely complex pathogen spectrum. Compared with conventional etiological detection methods, metagenomic next-generation sequencing (mNGS) enables rapid and broad-spectrum pathogen identification. However, compared with bronchoalveolar lavage fluid (BALF), research on the diagnostic value of sputum - used as a non-invasive sample - for pulmonary infections in KTRs remains limited. Methods: A retrospective study included 77 kidney transplant recipients (KTRs) with pulmonary infections admitted from July 2021 to January 2025. BALF (n=37) or sputum (n=40) was collected for mNGS. Ninety-two non-immunosuppressed patients with pulmonary infections, treated during the same period and with BALF for mNGS, were also included. We compared pathogen profiles between the two groups and evaluated the diagnostic performance for KTRs pulmonary infections between BALF and sputum. Results: The pathogen spectrum in KTRs was dominated by viruses (43.0%) and opportunistic fungi (20.0%), whereas bacteria (67.97%) predominated in the non-immunosuppressed group. The co-infection rate was significantly higher in KTRs than in the non-immunosuppressed group (67.57% vs. 35.87%, P<0.001). In the KTRs cohort, the sputum group had a much higher prevalence of heart disease than the BALF group (52.5% vs. 2.7%, P<0.001). The positive detection rates of sputum and BALF mNGS showed no statistical difference (97.5% vs. 91.89%, P = 0.268), but sputum mNGShad a higher concordance rate with the clinical composite diagnosis (95.0%) compared to BALF mNGS (81.08%). In both specimen types, mNGS achieved a significantly higher pathogen detection rate than conventional tests (P<0.001 for both), with poor agreement between the two approaches (Kappa < 0.2). Conclusion: The pathogen spectrum of pulmonary infections in KTRs differs significantly from that in non-immunosuppressed patients. It is characterized by a predominance of viruses and opportunistic fungi. mNGS is superior to conventional methods for making an etiological diagnosis. Non-invasive sputum mNGS is a valuable diagnostic alternative in KTRs, particularly for patients unable or unwilling to undergo invasive procedures.